<p>
  The use of alternative data sets to forecast stock prices has increased in recent years as the fundamental and 
  technical analysis spaces increase in competition. Utilizing Natural Language Processing (NLP) techniques to 
  analyze the sentiment of news releases and other text related to publicly traded companies has caught the interest
  of many quant researchers. Such online information is frequently released and can be interpreted in a virtually 
  unlimited number of ways, leading to a novel approach to determining the "societal mood" (Isah et al, 2018, p. 2)
  towards a company.
</p>

<p>
  There are several ways to implement a NLP system. In this tutorial, we utilize a dictionary to quantify the 
  sentiment of news releases. The dictionary provided herein was sourced from Isah et al (2018), where it's use 
  achieved a 70% accuracy when targeting several hand-picked stocks in India's pharmaceutical industry.
</p>